Rotation Correction Method Using Depth-Value Symmetry of Human Skeletal Joints for Single RGB-D Camera System

Abstract

Most red-green-blue and depth (RGB-D) motion-recognition technologies employ both depth and RGB cameras to recognize a user's body. However, motion-recognition solutions using a single RGB-D camera struggle with rotation recognition depending on the device-user distance and field-of-view. This paper proposes a near-real-time rotational-coordinate-correction method that rectifies a depth error unique Microsoft Kinect by using the symmetry of the depth coordinates of the human body. The proposed method is most effective within 2 m, a key range in which the unique depth error of Kinect occurs, and is anticipated to be utilized in applications requiring low cost and fast installation. It could also be useful in areas such as media art that involve unspecified users because it does not require a learning phase. Experimental results indicate that the proposed method has an accuracy of 85.38%, which is approximately 12% higher than that of the reference installation method.

Keywords

• human recognition systems
• kinect
• kinect depth error
• near-real-time
• RGB-D camera
• rotation correlation